In fact, this idea that input stimuli can be connected not only
by sharing common features, but also in terms of transformations
that map representations onto each other arises in at least
a couple of other domains.
In analogical reasoning, for example, knowledge from a familiar
base domain is leveraged in a novel target domain by identifying
a mapping from one to the other [1]}.
Thus, analogy overcomes the limits of simple featural similarity
in a comparable manner to that being discussed here in regards
to artificial neural networks.
In addition, transformations are frequently invoked to
connect distinct grammatical structures in natural languages.
So, passivisation - e.g. from John loves Mary to
Mary is loved by John - is a transformation that
preserves the basic semantics of sentences.
[2]} have proposed an approach to semantic parsing
based on treating such transformations as symmetries.
